Data Scientist II: AI & NLP at Scale

Scribd, Inc.; Portland (OR); Hybrid; USD 97,000 - 175,000; Full time

Benefits offered by this job

Scribd Flex

Health, dental, vision coverage

Paid time off

Parental leave

Employee equity

Learning & development

Wellness stipends

AI tools access

Job summary

Scribd, Inc. is seeking a Data Scientist II to design and deploy high‑impact AI/ML systems using massive data, language models and end‑to‑end deployments. You’ll work with ML Engineers, Data Engineers and Product to deliver scalable content classification solutions across text, image and audio domains.

The role emphasizes collaboration, simplicity, and measurable impact, with opportunities to leverage Scribd’s Mix of research and production workflows across multiple products.

Qualifications

• 3+ years of post qualification experience developing ML models and deploying to production.
• Proficiency in Python and experience with distributed data processing frameworks like Spark.
• Experience with NLP, information retrieval, or generative models is preferred.
• SQL or PySpark experience and a quantitative degree in a relevant field.

Responsibilities

• Focus on content classification use cases using traditional NLP and LLMs.
• Design and deploy high impact AI/ML systems in cross‑functional teams.
• Collaborate with Data Scientists, ML Engineers and Product partners on projects.
• Work with Python, SQL, Spark and various ML frameworks to process large data.

Skills

Python

Spark

SQL

NLP

Deep Learning

Generative Models

Education

Bachelor's or Master's in Statistics/CS/DS/AI

Tools

Databricks

PyTorch

LLM APIs

Scikit-learn

Job description

Scribd, Inc. is seeking a Data Scientist II to design and deploy high‑impact AI/ML systems using massive data, language models and end‑to‑end deployments. You’ll work with ML Engineers, Data Engineers and Product to deliver scalable content classification solutions across text, image and audio domains.

The role emphasizes collaboration, simplicity, and measurable impact, with opportunities to leverage Scribd’s Mix of research and production workflows across multiple products.